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Twentieth-century global-mean sea level rise: Is the whole greater than the sum of the parts?

Confidence in projections of global-mean sea level rise (GMSLR) depends on an ability to account for GMSLR during the twentieth century. There are contributions from ocean thermal expansion, mass loss from glaciers and ice sheets, groundwater extraction, and reservoir impoundment. Progress has been made toward solving the “enigma” of twentieth-century GMSLR, which is that the observed GMSLR has previously been found to exceed the sum of estimated contributions, especially for the earlier decades. The authors propose the following: thermal expansion simulated by climate models may previously have been underestimated because of their not including volcanic forcing in their control state; the rate of glacier mass loss was larger than previously estimated and was not smaller in the first half than in the second half of the century; the Greenland ice sheet could have made a positive contribution throughout the century; and groundwater depletion and reservoir impoundment, which are of opposite sign, may have been approximately equal in magnitude. It is possible to reconstruct the time series of GMSLR from the quantified contributions, apart from a constant residual term, which is small enough to be explained as a long-term contribution from the Antarctic ice sheet. The reconstructions account for the observation that the rate of GMSLR was not much larger during the last 50 years than during the twentieth century as a whole, despite the increasing anthropogenic forcing. Semiempirical methods for projecting GMSLR depend on the existence of a relationship between global climate change and the rate of GMSLR, but the implication of the authors' closure of the budget is that such a relationship is weak or absent during the twentieth century.

Journal of Climate

Climate model assessment of changes in winter-spring streamflow timing over North America

Over regions where snow-melt runoff substantially contributes to winter-spring streamflows, warming can accelerate snow melt and reduce dry-season streamflows. However, conclusive detection of changes and attribution to anthropogenic forcing is hindered by brevity of observational records, model uncertainty, and uncertainty concerning internal variability. In this study, a detection/attribution of changes in mid-latitude North American winter-spring streamflow timing is examined using nine global climate models under multiple forcing scenarios. In this study, robustness across models, start/end dates for trends, and assumptions about internal variability is evaluated. Marginal evidence for an emerging detectable anthropogenic influence (according to four or five of nine models) is found in the north-central U.S., where winter-spring streamflows have been coming earlier. Weaker indications of detectable anthropogenic influence (three of nine models) are found in the mountainous western U.S./southwestern Canada and in extreme northeastern U.S./Canadian Maritimes. In the former region, a recent shift toward later streamflows has rendered the full-record trend toward earlier streamflows only marginally significant, with possible implications for previously published climate change detection findings for streamflow timing in this region. In the latter region, no forced model shows as large a shift toward earlier streamflow timing as the detectable observed shift. In other (including warm, snow-free) regions, observed trends are typically not detectable, although in the U.S. central plains we find detectable delays in streamflow, which are inconsistent with forced model experiments.

Journal of Climate

Attribution analysis of the Ethiopian drought of 2015

In northern and central Ethiopia, 2015 was a very dry year. Rainfall was only from one-half to three-quarters of the usual amount, with both the “belg” (February–May) and “kiremt” rains (June–September) affected. The timing of the rains that did fall was also erratic. Many crops failed, causing food shortages for many millions of people. The role of climate change in the probability of a drought like this is investigated, focusing on the large-scale precipitation deficit in February–September 2015 in northern and central Ethiopia. Using a gridded analysis that combines station data with satellite observations, it is estimated that the return period of this drought was more than 60 years (lower bound 95% confidence interval), with a most likely value of several hundred years. No trend is detected in the observations, but the large natural variability and short time series means large trends could go undetected in the observations. Two out of three large climate model ensembles that simulated rainfall reasonably well show no trend while the third shows an increased probability of drought. Taking the model spread into account the drought still cannot be clearly attributed to anthropogenic climate change, with the 95% confidence interval ranging from a probability decrease between preindustrial and today of a factor of 0.3 and an increase of a factor of 5 for a drought like this one or worse. A soil moisture dataset also shows a nonsignificant drying trend. According to ENSO correlations in the observations, the strong 2015 El Niño did increase the severity of the drought.

Journal of Climate

Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model

Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.

Florida

The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

Journal of Climate

Detection and attribution of temperature changes in the mountainous Western United States

Large changes in the hydrology of the western United States have been observed since the mid-twentieth century. These include a reduction in the amount of precipitation arriving as snow, a decline in snowpack at low and midelevations, and a shift toward earlier arrival of both snowmelt and the centroid (center of mass) of streamflows. To project future water supply reliability, it is crucial to obtain a better understanding of the underlying cause or causes for these changes. A regional warming is often posited as the cause of these changes without formal testing of different competitive explanations for the warming. In this study, a rigorous detection and attribution analysis is performed to determine the causes of the late winter/early spring changes in hydrologically relevant temperature variables over mountain ranges of the western United States. Natural internal climate variability, as estimated from two long control climate model simulations, is insufficient to explain the rapid increase in daily minimum and maximum temperatures, the sharp decline in frost days, and the rise in degree-days above 0??C (a simple proxy for temperature driven snowmelt). These observed changes are also inconsistent with the model-predicted responses to variability in solar irradiance and volcanic activity. The observations are consistent with climite simulations that include the combined effects of anthropogenic greenhouse gases and aerosols. It is found that, for each temperature variable considered, an anthropogenic signal is identifiable in observational fields. The results are robust to uncertainties in model-estimated fingerprints and natural variability noise, to the choice of statistical down-scaling method, and to various processing options in the detection and attribution method. ?? 2008 American Meteorological Society.

Journal of Climate

GFDL's CM2 global coupled climate models. Part I: Formulation and simulation characteristics

The formulation and simulation characteristics of two new global coupled climate models developed at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) are described. The models were designed to simulate atmospheric and oceanic climate and variability from the diurnal time scale through multicentury climate change, given our computational constraints. In particular, an important goal was to use the same model for both experimental seasonal to interannual forecasting and the study of multicentury global climate change, and this goal has been achieved. Tw o versions of the coupled model are described, called CM2.0 and CM2.1. The versions differ primarily in the dynamical core used in the atmospheric component, along with the cloud tuning and some details of the land and ocean components. For both coupled models, the resolution of the land and atmospheric components is 2?? latitude ?? 2.5?? longitude; the atmospheric model has 24 vertical levels. The ocean resolution is 1?? in latitude and longitude, with meridional resolution equatorward of 30?? becoming progressively finer, such that the meridional resolution is 1/3?? at the equator. There are 50 vertical levels in the ocean, with 22 evenly spaced levels within the top 220 m. The ocean component has poles over North America and Eurasia to avoid polar filtering. Neither coupled model employs flux adjustments. The co ntrol simulations have stable, realistic climates when integrated over multiple centuries. Both models have simulations of ENSO that are substantially improved relative to previous GFDL coupled models. The CM2.0 model has been further evaluated as an ENSO forecast model and has good skill (CM2.1 has not been evaluated as an ENSO forecast model). Generally reduced temperature and salinity biases exist in CM2.1 relative to CM2.0. These reductions are associated with 1) improved simulations of surface wind stress in CM2.1 and associated changes in oceanic gyre circulations; 2) changes in cloud tuning and the land model, both of which act to increase the net surface shortwave radiation in CM2.1, thereby reducing an overall cold bias present in CM2.0; and 3) a reduction of ocean lateral viscosity in the extratropics in CM2.1, which reduces sea ice biases in the North Atlantic. Both models have be en used to conduct a suite of climate change simulations for the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment report and are able to simulate the main features of the observed warming of the twentieth century. The climate sensitivities of the CM2.0 and CM2.1 models are 2.9 and 3.4 K, respectively. These sensitivities are defined by coupling the atmospheric components of CM2.0 and CM2.1 to a slab ocean model and allowing the model to come into equilibrium with a doubling of atmospheric CO2. The output from a suite of integrations conducted with these models is freely available online (see http://nomads.gfdl.noaa.gov/). ?? 2006 American Meteorological Society.

Journal of Climate

Applying downscaled Global Climate Model data to a groundwater model of the Suwannee River Basin, Florida, USA

The application of Global Climate Model (GCM) output to a hydrologic model allows for comparisons between simulated recent and future conditions and provides insight into the dynamics of hydrology as it may be affected by climate change. A previously developed numerical model of the Suwannee River Basin, Florida, USA, was modified and calibrated to represent transient conditions. A simulation of recent conditions was developed for the 372-month period 1970-2000 and was compared with a simulation of future conditions for a similar-length period 2039-2069, which uses downscaled GCM data. The MODFLOW groundwater-simulation code was used in both of these simulations, and two different MODFLOW boundary condition “packages” (River and Streamflow-Routing Packages) were used to represent interactions between surface-water and groundwater features. The hydrologic fluxes between the atmosphere and landscape for the simulation of future conditions were developed from dynamically downscaled precipitation and evapotranspiration (ET) data generated by the Community Climate System Model (CCSM). The downscaled precipitation data were interpolated for the Suwannee River model grid, and the downscaled ET data were used to develop potential ET and were interpolated to the grid. The fu¬ture period has higher simulated rainfall (10.8 percent) and ET (4.5 percent) than the recent period. The higher future rainfall causes simulated groundwater levels to rise in areas where they are deep and have little ET in either the recent or future case. However, in areas where groundwater levels were originally near the surface, the greater future ET causes groundwater levels to become lower despite the higher projected rainfall. The general implication is that unsaturated zone depth could be more spatially uniform in the future and vegetation that requires a range of conditions (substantially wetter or drier than aver¬age) could be detrimentally affected. This vegetation would include wetland species, especially in areas inland from the coast.

Florida

The new GFDL global atmosphere and land model AM2-LM2: Evaluation with prescribed SST simulations

The configuration and performance of a new global atmosphere and land model for climate research developed at the Geophysical Fluid Dynamics Laboratory (GFDL) are presented. The atmosphere model, known as AM2, includes a new gridpoint dynamical core, a prognostic cloud scheme, and a multispecies aerosol climatology, as well as components from previous models used at GFDL. The land model, known as LM2, includes soil sensible and latent heat storage, groundwater storage, and stomatal resistance. The performance of the coupled model AM2-LM2 is evaluated with a series of prescribed sea surface temperature (SST) simulations. Particular focus is given to the model's climatology and the characteristics of interannual variability related to El Nin??o-Southern Oscillation (ENSO). One AM2-LM2 integration was perfor med according to the prescriptions of the second Atmospheric Model Intercomparison Project (AMIP II) and data were submitted to the Program for Climate Model Diagnosis and Intercomparison (PCMDI). Particular strengths of AM2-LM2, as judged by comparison to other models participating in AMIP II, include its circulation and distributions of precipitation. Prominent problems of AM2-LM2 include a cold bias to surface and tropospheric temperatures, weak tropical cyclone activity, and weak tropical intraseasonal activity associated with the Madden-Julian oscillation. An ensemble of 10 AM2-LM 2 integrations with observed SSTs for the second half of the twentieth century permits a statistically reliable assessment of the model's response to ENSO. In general, AM2-LM2 produces a realistic simulation of the anomalies in tropical precipitation and extratropical circulation that are associated with ENSO. ?? 2004 American Meteorological Society.

Journal of Climate

Storm surges and climate change implications for tidal marshes: Insight from the San Francisco Bay Estuary, California, USA

Tidal marshes are dynamic ecosystems, which are influenced by oceanic and freshwater processes and daily changes in sea level. Projected sea-level rise and changes in storm frequency and intensity will affect tidal marshes by altering suspended sediment supply, plant communities, and the inundation duration and depth of the marsh platform. The objective of this research was to evaluate if regional weather conditions resulting in low-pressure storms changed tidal conditions locally within three tidal marshes. We hypothesized that regional storms will increase sea level heights locally, resulting in increased inundation of the tidal marsh platform and plant communities. Using site-level measurements of elevation, plant communities, and water levels, we present results from two storm events in 2010 and 2011 from the San Francisco Bay Estuary (SFBE), California, USA. The January 2010 storm had the lowest recorded sea level pressure in the last 30 years for this region. During the storm episodes, the duration of tidal marsh inundation was 1.8 and 3.1 times greater than average for that time of year, respectively. At peak storm surges, over 65% in 2010 and 93% in 2011 of the plant community was under water. We also discuss the implications of these types of storms and projected sea-level rise on the structure and function of the tidal marshes and how that will impact the hydro-geomorphic processes and marsh biotic communities.

California

The leading mode of observed and CMIP5 ENSO-residual sea surface temperatures and associated changes in Indo-Pacific climate

SSTs in the western Pacific Ocean have tracked closely with CMIP5 simulations despite recent hiatus cooling in the eastern Pacific. This paper quantifies these similarities and associated circulation and precipitation variations using the first global 1900–2012 ENSO-residual empirical orthogonal functions (EOFs) of 35 variables: observed SSTs; 28 CMIP5 SST simulations; Simple Ocean Data Assimilation (SODA) 25-, 70-, and 171-m ocean temperatures and sea surface heights (SSHs); and Twentieth Century Reanalysis, version 2 (20CRv2), surface winds and precipitation. While estimated independently, these leading EOFs across all variables fit together in a meaningful way, and the authors refer to them jointly as the west Pacific warming mode (WPWM). WPWM SST EOFs correspond closely in space and time. Their spatial patterns form a “western V” extending from the Maritime Continent into the extratropical Pacific. Their temporal principal components (PCs) have increased rapidly since 1990; this increase has been primarily due to radiative forcing and not natural decadal variability. WPWM circulation changes appear consistent with a Matsuno–Gill-like atmospheric response associated with an ocean–atmosphere dipole structure contrasting increased (decreased) western (eastern) Pacific precipitation, SSHs, and ocean temperatures. These changes have enhanced the Walker circulation and modulated weather on a global scale. An AGCM experiment and the WPWM of global boreal spring precipitation indicate significant drying across parts of East Africa, the Middle East, the southwestern United States, southern South America, and Asia. Changes in the WPWM have tracked closely with precipitation and the increase in drought frequency over the semiarid and water-insecure areas of East Africa, the Middle East, and southwest Asia.

Journal of Climate

Methodology and results of calculating central California surface temperature trends: Evidence of human-induced climate change?

A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910-2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25??C decade-1). The Valley trend of annual mean temperatures is +0.07?? ?? 0.07??C decade-1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02?? ?? 0.10??C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4??C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain. ?? 2006 American Meteorological Society.

Journal of Climate

Prediction of summer maximum and minimum temperature over the central and western United States: The roles of soil moisture and sea surface temperature

A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.

Western United States

Climatic controls on the snowmelt hydrology of the northern Rocky Mountains

The northern Rocky Mountains (NRMs) are a critical headwaters region with the majority of water resources originating from mountain snowpack. Observations showing declines in western U.S. snowpack have implications for water resources and biophysical processes in high-mountain environments. This study investigates oceanic and atmospheric controls underlying changes in timing, variability, and trends documented across the entire hydroclimatic-monitoring system within critical NRM watersheds. Analyses were conducted using records from 25 snow telemetry (SNOTEL) stations, 148 1 April snow course records, stream gauge records from 14 relatively unimpaired rivers, and 37 valley meteorological stations. Over the past four decades, midelevation SNOTEL records show a tendency toward decreased snowpack with peak snow water equivalent (SWE) arriving and melting out earlier. Temperature records show significant seasonal and annual decreases in the number of frost days (days ≤0°C) and changes in spring minimum temperatures that correspond with atmospheric circulation changes and surface–albedo feedbacks in March and April. Warmer spring temperatures coupled with increases in mean and variance of spring precipitation correspond strongly to earlier snowmeltout, an increased number of snow-free days, and observed changes in streamflow timing and discharge. The majority of the variability in peak and total annual snowpack and streamflow, however, is explained by season-dependent interannual-to-interdecadal changes in atmospheric circulation associated with Pacific Ocean sea surface temperatures. Over recent decades, increased spring precipitation appears to be buffering NRM total annual streamflow from what would otherwise be greater snow-related declines in hydrologic yield. Results have important implications for ecosystems, water resources, and long-lead-forecasting capabilities.

Idaho, Montana

Changes in the proportion of precipitation occurring as snow in New England (1949-2000)

The ratio of snow to total precipitation (S/P) is a hydrologic indicator that is sensitive to climate variability and can be used to detect and monitor hydrologic responses to climatic change. Changes in S/P ratio over time could influence the magnitude and timing of spring runoff and recession to summer baseflow. The S/P ratio for 21 U.S. Historical Climatology Network sites in New England was examined. Eleven out of twenty-one sites in New England had significant decreasing annual S/P ratios from 1949 to 2000. Annual trends in S/P are predominantly a result of decreasing snowfall, and to a lesser extent, increasing rainfall. The most consistent trends were in northernmost New England where all four sites had decreasing ratios, and in the coastal and near-coastal areas where five out of eight sites had significantly decreasing ratios. The four sites in northernmost New England, which had the strongest and most coherent trends, showed an average decrease in annual S/P ratio from about 0.30 in 1949 to 0.23 in 2000. Trends in winter S/P ratio were less geographically consistent. Seven out of 21 sites had significantly decreasing winter S/P ratios. Most northern New England and coastal to near-coastal sites had statistically significant trends (p < 0.05) or weak, but not significant trends (p < 0.2). When trends in S/P were analyzed on a monthly basis for the northernmost sites, it was evident that decreasing S/P trends were significant for March and December only. Significant correlations were observed between winter S/P ratios in northern New England and the timing of spring runoff, the North Atlantic Oscillation (NAO) index, and the Pacific-North American (PNA) index. Significant correlations were observed between winter S/P ratios averaged for all of New England and the NAO and PNA.

Journal of Climate

Interannual climate variability and snowpack in the western United States

An important part of the water supply in the western United States is derived from runoff fed by mountain snowmelt Snow accumulation responds to both precipitation and temperature variations, and forms an interesting climatic index, since it integrates these influences over the entire late fall-spring period. Here, effects of cool season climate variability upon snow water equivalent (SWE) over the western part of the conterminous United States are examined. The focus is on measurements on/and 1 April, when snow accumulation is typically greatest. The primary data, from a network of mountainous snow courses, provides a good description of interannual fluctuations in snow accumulations, since many snow courses have records of five decades or more. For any given year, the spring SWE anomaly at a particular snow course is likely to be 25%&ndash;60% of its long-term average. Five separate regions of anomalous SWE variability are distinguished, using a rotated principal components analysis. Although effects vary with region and with elevation, in general, the anomalous winter precipitation has the strongest influence on spring SWE fluctuations. Anomalous temperature has a weaker effect overall, but it has great influence in lower elevations such as in the coastal Northwest, and during spring in higher elevations. The regional snow anomaly patterns are associated with precipitation and temperature anomalies in winter and early spring. Patterns of the precipitation, temperature, and snow anomalies extend over broad regional areas, much larger than individual watersheds. These surface anomalies are organized by the atmospheric circulation, with primary anomaly centers over the North Pacific Ocean as well as over western North America. For most of the regions, anomalously low SWE is associated with a winter circulation resembling the PNA pattern. With a strong low in the central North Pacific and high pressure over the Pacific Northwest, this pattern diverts North Pacific storms northward, away from the region. Both warm and cool phases of El Ni&ntilde;o-Southern Oscillation tend to produce regional patterns with out-of-phase SWE anomalies in the Northwest and the Southwest.

Arizona, California, Colorado, Idaho, Montana, Nev

Pacific sea surface temperature linkages with Tanzania’s multi-season drying trends

Droughts in Tanzania pose challenges to agriculture, water resources, and hydropower production, all of which impact livelihoods. Tanzania experienced below average precipitation during 1999-2014 during two important seasons: December to February (DJF) in the south and during March to June (MAMJ) in the northeast. We explore DJF and MAMJ precipitation in the areas with drying trends and examine their relationships with anomalous sea surface temperatures (SST) in the Indo-Pacific and corresponding circulation patterns. It is found that at seasonal time scales, precipitation in DJF and MAMJ trend areas appears inversely related to diabatic forcing in the equatorial Pacific. The dominant influence for droughts in DJF is from eastern Pacific SST while for droughts in MAMJ it is from West Pacific SST. A bivariate regression model with West Pacific and Niño3.4 region SST as predictors is found to recreate multidecadal DJF variability after the 1950s and the extreme drying in MAMJ during the 2000s. The regression model coefficients also indicate differential eastern vs. western Pacific forcing for DJF vs. MAMJ. Thus we suggest that recent La Niña-like conditions, characterized by an enhanced Pacific SST gradient due to cooling in the eastern Pacific and warming in the western Pacific, played a substantial role in Tanzania’s recent multi-season drying trends. SST change scenarios (difference between 2023-2037 and 2000-2014 means) based on CMIP5 projections and observed trends illustrate the uncertainty about future precipitation outcomes and also the potential implications of contrasting linkages to eastern vs. western Pacific SSTs. These scenarios are mainly optimistic for the DJF southern Tanzania trend area, because it appears dominated by Niño3.4 cooling at both seasonal and decadal time scales. Conversely, our scenarios are quite pessimistic for the MAMJ northeastern Tanzania trend area, because we find a dominant negative influence of warming West Pacific SST.

International Journal of Climate Change: Impacts a

Large-scale atmospheric forcing of recent trends toward early snowmelt runoff in California

Since the late 1940s, snowmelt and runoff have come increasingly early in the water year in many basins in northern and central California. This subtle trend is most pronounced in moderate-altitude basins, which are sensitive to changes in mean winter temperatures. Such basins have broad areas in which winter temperatures are near enough to freezing that small increases result initially in the formation of less snow and eventually in early snowmelt. In moderate-altitude basins of California, a declining fraction of the annual runoff has come in April–June. This decline has been compensated by increased fractions of runoff at other, mostly earlier, times in the water year. Weather stations in central California, including the central Sierra Nevada, have shown trends toward warmer winters since the 1940s. A series of regression analyses indicate that runoff timing responds equally to the observed decadal-scale trends in winter temperature and interannual temperature variations of the same magnitude, suggesting that the temperature trend is sufficient to explain the runoff-timing trends. The immediate cause of the trend toward warmer winters in California is a concurrent, long-term fluctuation in winter atmospheric circulations over the North Pacific Ocean and North America that is not immediately distinguishable from natural atmospheric variability. The fluctuation began to affect California in the 1940s, when the region of strongest low-frequency variation of winter circulations shifted to a part of the central North Pacific Ocean that is teleconnected to California temperatures. Since the late 1940s, winter wind fields have been displaced progressively southward over the central North Pacific and northward over the west coast of North America. These shifts in atmospheric circulations are associated with concurrent shifts in both West Coast air temperatures and North Pacific sea surface temperatures.

California